Vast volumes of heterogeneous data sets generated from diverse security devices, network infrastructure, systems and applications, are collected.

Log and event data collected are compressed at a ratio of up to 96%, digitally signed and optionally encrypted before they are archived. This way, collected log and event data and maintained in a state that could also be utilized for forensic investigation or legal evidence, should the need arise.

Log and event data collected are normalized and stored into a common schema, at the time of data collection, for further processing.

Intelligent processing, aggregation and analysis of log and event data with the use of User & Entity Behavioral, Artificial Intelligence, Predictive and Machine Learning models by incorporating contextual information for the prediction of suspicious and/or the detection of abnormal behavior.

Correlation of log and event data utilizes, not only a number of statistical and heuristic models, but also a number of predefined intelligent correlation rules combined with evidence-based knowledge of emerging threats and vulnerabilities, this way allowing the early detection of and response to targeted attacks and data breaches.

Sensitive information found within log and event data, such as credit card numbers, can be optionally masked to safeguard confidentiality.